Social Science Electronic Publishing
The extant literature using household scanner data to estimate consumer choice models has identified two key sources of bias in estimated mean responses to marketing variables. Omitted heterogeneity may bias mean responses towards zero. At the same time, omitted time-varying characteristics of alternatives that influence consumer choices may also bias mean responses towards zero if these characteristics are correlated with observed factors such as price - the endogeneity bias. Both these issues have been well recognized, and methods have been proposed to address them using household scanner panel data. While discussing the relative merits of household data to estimate the distribution of heterogeneity and store-level data to address the endogeneity problem, this paper proposes an integrated estimation procedure that uses the information in both sources. The approach provides consistent estimates of the mean responses to marketing variables and the heterogeneity distribution and controls for potential endogeneity due to correlation between unmeasured item-level characteristics and prices.